We might be able to do better at conflict resolution — making peace in violent conflicts — with the help of good data analysis. There have long been data sets about war and violent conflict at the state level, but we now have much more.

There are now extraordinarily detailed, open-source event data streams that can be used for violence prediction. Conflict “microdata” from social media and communications records can be used to visualize the divisions in society. I also suggest a long term program of conflict data collection to learn, over many cases, what works in conflict resolution and what doesn’t.

We’re really just at the beginning of all of this. There are huge issues around data collection, interpretation, privacy, security, and politics. But the potential is too great to ignore.

Update: two excellent resources have come to my attention in the days since I gave this talk (which is, of course, part of why I give talks.)

First, see the International Peace Institute’s paper on Big Data for Conflict Prevention. This paper was co-authored by Patrick Meier, who has been deeply involved in the crisis mapping work I mentioned in my talk.

But even more awesome, Erica Chenoweth has done exactly the sort of data-driven case-control study I was contemplating in my talk, and shown that non-violent political resistance succeeds twice as often as armed resistance. Her data set, the Nonviolent and Violent Campaigns and Outcomes (NAVCO) Data Project, also shows that non-violence is much more likely to lead to good democracies five years later, and that a movement that can recruit 10% of the population is almost guaranteed to succeed.